I will build a rag-powered AI chatbot that answers questions from your documents

Tired of employees wasting time searching through PDFs, manuals, or internal docs? I'll build you a production-ready RAG (Retrieval-Augmented Generation) chatbot that lets users ask plain-English questions and get accurate answers — pulled directly from YOUR documents.

This is not a generic ChatGPT wrapper. I build a proper pipeline: your docs get chunked, embedded, stored in a vector database (pgvector), and queried via a LangChain-powered retrieval chain with a FastAPI backend.

WHAT YOU GET:

1. Fully working RAG pipeline (ingest, embed, retrieve, answer)
2. FastAPI backend with clean REST endpoints
3. Support for PDF, DOCX, or TXT documents
4. Choice of LLM: OpenAI GPT-4o OR on-premise/open-source model (Ollama/Gemma) for data-sensitive use cases
5. Clean API documentation (Postman collection)
6. Deployment-ready Docker setup
7. Source code with comments + handover notes

MY APPROACH:

I design systems that are deterministic and reliable, not just "demos." Every pipeline I build includes chunking strategy tuned to your document type, embedding model selection, and retrieval testing before handover.

I've built production IDP and RAG systems at Dassault Systemes and have hands-on experience with LangChain, LangGraph, pgvector, Azure Document Intelligence, and Ollama.

NOT INCLUDED (but available as extras):

- Frontend UI/chat interface

- Integration with Slack/Teams

- Multi-language support

MESSAGE ME BEFORE ORDERING — I'll review your use case and confirm the right scope for your project.